Skip to main content
Glama

Rhea

by io.github.pipeworx-io

Polymarket Edge Tracker

polymarket_edge_tracker
Read-onlyIdempotent

Edge persistence and decay telemetry built from daily polymarket_edges snapshots. Answers "how long has this edge existed and is it shrinking?" — a fresh wide edge and a 3-week-old wide edge are different trades (the latter is wide for a reason nobody is willing to take). Args: days (lookback, default 14, max 30), window (snapshot family, default "1wk"). RESPONSE: tracked[] = every opportunity in the LATEST snapshot with its full edge_pp_net time-series across prior snapshots, first_seen, trend (new | widening | stable | decaying) and decay_pp_per_day (both computed on |edge_pp_net| — the value itself is signed by trade direction, negative = SELL YES); expired[] = opportunities that appeared in earlier snapshots but are GONE from the latest (closed, resolved, or arbed away) with their lifespan_days — the median lifespan is your competition clock; snapshot_dates[] = which days actually have data (snapshots are written when polymarket_edges runs on a cache-miss, so gaps mean nobody scanned that day). LIMITS: history depth is bounded by the 60-day snapshot TTL and starts from when snapshotting was enabled; decay numbers come from daily closes of edge_pp_net (net of default slippage), not intraday.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoLookback in days (default 14, clamp 2-30).
windowNoWhich polymarket_edges window family to read snapshots for: 24hr | 1wk | 1mo (default 1wk).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnlyHint, idempotentHint, and non-destructive. The description adds significant value by explaining the response structure (tracked[], expired[], snapshot_dates[]), the meaning of decay_pp_per_day (negative = SELL YES), and limitations (60-day TTL, no intraday). No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well front-loaded with the core purpose and includes necessary technical details. It is slightly dense but every sentence adds value. Could benefit from slight restructuring for readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite lacking an output schema, the description thoroughly explains all response fields (tracked, expired, snapshot_dates) and their semantics. It also covers limitations and edge cases (e.g., gaps in snapshots). Complete for a read-only telemetry tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with parameter descriptions. The description adds extra context beyond the schema, such as default values (14 for days, '1wk' for window), bounds (max 30, clamp 2-30), and explanation of 'window' as snapshot family.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states 'Edge persistence and decay telemetry' and answers a specific question about edge longevity. It distinguishes itself from the sibling 'polymarket_edges' by focusing on historical tracking vs. current edges.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on when to use this tool (e.g., evaluating whether a wide edge is fresh or old). Implicitly distinguishes from 'polymarket_edges', but lacks explicit 'when not to use' or alternative recommendations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Rhea toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.9/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, with only minor overlap between similar variants (e.g., ask_pipeworx variants) and related prediction market tools (bet_research vs polymarket_edges). Overall, an agent can reliably select the right tool.

Naming Consistency3/5

Tool names mix verb_noun (e.g., resolve_entity), noun_noun (e.g., entity_profile), and adjective_noun (e.g., recent_changes) patterns, plus a few single verbs. While readable, the lack of a uniform convention adds ambiguity.

Tool Count3/5

33 tools is large but justified by the broad domain coverage. The count is borderline high but still manageable with meta-tools (ask_pipeworx, deep_research) that reduce the effective surface.

Completeness4/5

The tool set covers a wide range of data sources and tasks, with meta-tools providing deep coverage. Minor gaps exist (e.g., no dedicated Kalshi-only tools, limited attention to non-Polymarket prediction markets), but the overall surface is thorough.

Resources